Artificial intelligence for the automation of services in distributed network infrastructures

Sensory insert for plastic injection molding with complete thin-film sensor system.
© Fraunhofer IST
Sensory insert for plastic injection molding with complete thin-film sensor system.
Das 9. Ziel für nachhaltige Entwicklung der UN: Industrie, Innovation und Infrastruktur.


Digitalization is of enormous importance, and developments such as robotics and Industry 4.0 will continue to exert a significant influence on our lives. In the “ANIARA” project, the Fraunhofer IST is working on the development and interconnection of intelligent thin-film sensors for automated, wireless data exchange on the basis of concrete use cases in the context of production technology.


ANIARA brings together three fields of technology: Communication networks and technologies for 5G and prospectively 6G, usage-related data centers, and artificial intelligence (AI). The Fraunhofer IST will thereby develop real-time-capable sensor systems which can be integrated into existing infrastructures and utilized for data analysis with AI algorithms. By means of automated error detection and the derivation of virtual product properties, optimal operating strategies are to be developed and the entire process chain monitored.

Added value 

The results of the research project enable a systematic and goal-oriented development and interconnection of real-time-capable thin-film sensors to automated network and communication structures. Consequently, the generated sensor and measurement data can be used more efficiently and comprehensively in the future, including across different locations.

Insights into the project

Concept ANIARA
© IWF TU Braunschweig
Schematic representation of network levels for different devices and services.

Further information



Anna-Sophia Wilde, Marvin Czarski, Anna Schott, Tim Abraham, Christoph Herrmann

Utilizing Artificial Intelligence for Virtual Quality Gates in Changeable Production Systems.

In: Congress of the German Academic Association for Production Technology. Production at the Leading Edge of Technology  (2023) pp 484–493.

DOI: 10.1007/978-3-031-18318-8_49



Anna Schott, Martin Rekowski, Frederic Timmann, Christoph Herrmann, Klaus Dröder

Development of Thin-film Sensors for In-process Measurement during Injection Molding.

In: Procedia CIRP, Volume 120 (2023), Pages 619-6242023.

Funding reference



This project is being funded by the German Federal Ministry of Education and Research (BMBF).

We offer solutions for all your applications


Industry solutions

Digital economy